fix issue with incorrect rules added to strong_rules; keep subset for…

… each theorem to speed up structural inference

pynars/NARS/InferenceEngine/KanrenEngine/KanrenEngine.py

@@ -33,12 +33,12 @@ def __init__(self):
             higher_order.append(rule)
 
         # save subset for backward inference
-        self.rules_backward = [convert(r) for r in nal1_rules + nal2_rules 
+        self.rules_backward = [convert(r, True) for r in nal1_rules + nal2_rules 
                                + higher_order 
                             #    + conditional_syllogistic
                                ]
 
-        self.rules_conditional_syllogistic = [convert(r) for r in conditional_syllogistic]
+        self.rules_conditional_syllogistic = [convert(r, True) for r in conditional_syllogistic]
 
         for rule in nal3_rules:
             # replace --> with ==> and <-> with <=> in NAL3 (except difference)
@@ -251,8 +251,9 @@ def inference_structural(self, t: Sentence, theorems = None):
             theorems = self.theorems
 
         l1 = logic(t.term, structural=True)
-        for (l2, sub_terms) in theorems:
-            for rule in rules_strong:
+        for (l2, sub_terms, matching_rules) in theorems:
+            for i in matching_rules:
+                rule = rules_strong[i] 
                 res = self.apply(rule, l2, l1)
                 if res is not None:
                     # ensure no theorem terms in conclusion

pynars/NARS/InferenceEngine/KanrenEngine/util.py

@@ -125,8 +125,14 @@ def convert_theorems(theorem):
     # print(l)
     # print(term(l))
     # print("\n\n")
+    matching_rules = []
+    for i, rule in enumerate(rules_strong):
+        (p1, p2, c) = rule[0]
+        if run(1, c, eq(p1, l)):
+            matching_rules.append(i)
+
     sub_terms = frozenset(filter(lambda x: x != place_holder, t.sub_terms))
-    return (l, sub_terms)
+    return (l, sub_terms, tuple(matching_rules))
 
 
 #################